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POSTDOC IN FOREST REMOTE SENSING, MODELLING AND DEEP LEARNING (m/f)
Luxembourg Institute of Science and Technology - LIST
Luxembourg, ESCH-SUR-ALZETTE
emporary contract 75% part time position | 36 months | Belvaux
Are you passionate about research? So are we! Come and join us
The Luxembourg Institute of Science and Technology (LIST) is a leading Research and Technology Organisation (RTO) that drives innovation for the economy and society in Luxembourg and beyond. With cutting-edge expertise in Natural, Built, Industrial environments, Space, AI, Security and defence technologies. LIST bridges scientific excellence and applied research to design solutions that address real-world challenges and create positive impact.
Do you want to know more about LIST? Check our website: https://www.list.lu/
How will you contribute?
The Post-Doc researcher will develop, implement, and apply advanced ways in inverting a radiative transfer model for forest trait and uncertainty mapping at satellite, airborne and drone levels. You will explore advanced retrieval techniques, including spatio-temporal regularization, and hybrid methods with machine learning and deep learning. You will support the development of an improved forest RTM that can exploit LiDAR full-waveform data along with hyperspectral signatures. You will plan and carry out field campaigns in Austria and Luxembourg with drone, field, and laboratory measurements for validation of the model and retrieval results. The improved methods will be applied to multi- and hyperspectral satellite (Sentinel-2, PRISMA, EnMAP) data for showcasing the improved mapping and monitoring of forest traits and uncertainties.
You will be mainly in charge of:
• Develop improved hybrid model inversion methods with a focus on machine learning and deep learning and spatio-temporal regularisation
• Processing multi- and hyperspectral satellite and drone data
• Collection of field data on relevant forest traits and laboratory analysis
• Support the development of the forest radiative transfer modelling to simulate LiDAR signatures
• Lead publications in peer-reviewed journals
This position is part of an international research project together with BOKU Wien and GFZ Potsdam, jointly funded by the FNR, DFG, and FWF. We seek candidates with a strong potential to excel in a collaborative and multidisciplinary environment and use their skill for the benefit of society in the long term.
Is Your profile described below? Are you our future colleague? Apply now!
Education
• PhD degree in remote sensing, preferably with a doctoral thesis on RTM inversion or deep learning in remote sensing
Experience and skills
• Knowledge of quantitative remote sensing methods, particularly vegetation radiative transfer models (RTMs), and RTM inversion methods (LUT and hybrid approaches)
• Profound knowledge in machine learning and deep learning methods for remote sensing applications, including architectures such as CNNs, LSTMs, and Transformers, and deep generative models (e.g., VAEs, normalizing flows, diffusion models).
• Hands-on experience in multi- and hyperspectral image processing (e.g., IDL/ENVI) and RTM inversion (e.g., ARTMO)
• Proficiency in scientific programming using Python, with experience in Matlab and/or R considered an asset.
• Hands-on experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX.
• Experience in the organisation of field campaigns
• Solid publication record and good scientific writing skills
Language skills
Fluency in English AND , both oral and written.
Your LIST benefits
• An organization with a passion for impact and strong RDI partnerships in Luxembourg and Europe that works on responsible and independent research projects
• Sustainable by design, empowering our belief that we play an essential role in paving the way to a green society
• Innovative infrastructures and exceptional labs occupying more than 5,000 square metres, including innovations in all that we do
• An environment encouraging curiosity, innovation and entrepreneurship in all areas
• Personalized learning programme to foster our staff's soft and technical skills
• Multicultural and international work environment with more than 50 nationalities represented in our workforce
• Diverse and inclusive work environment empowering our people to fulfil their personal and professional ambitions
• Gender-friendly environment with multiple actions to attract, develop and retain women in science
• 32 days' paid annual leave, 11 public holidays, 13-month salary, statutory health insurance
• Flexible working hours, home working policy and access to lunch vouchers
Apply online
Your application must include:
• A motivation letter oriented towards the position and detailing your experience
• A scientific CV with contact details
• List of publications (and patents, if applicable)
• Contact details of 2 references
Please apply ONLINE formally through the HR system. Applications by email will not be considered.
Application procedure and conditions
• We kindly request applicants to provide their nationality for statistical purposes only, as part of our commitment to promoting diversity and ensuring equal opportunities in our workforce. This information will be kept confidential and will not be used for any discriminatory purposes.
• LIST is dedicated to maintaining an inclusive work environment and is an equal opportunity employer. We are committed to attracting, hiring, and retaining a diverse workforce. All applicants will be considered for employment without discrimination based on national origin, race, colour, gender, sexual orientation, gender identity, marital status, religion, age, or disability.
• Applications will be continuously reviewed until the position is filled. An assessment committee will thoroughly evaluate applications, adhering to guidelines designed to ensure equal opportunities. The primary criteria for selection will be the alignment of the applicant's existing skills and expertise with the requirements mentioned above.
Description des tâches:
AI Engineer (F/M)
adwäisEO Betzdorf (Luxembourg) CDI – Full Time
Asap 2-3 years of experience
The company
adwäisEO is a fast-growing company, leader in the sector of it services related to the Space Ground Segment. Its clients are Space Agencies (i.e. ESA and Luxembourg Space Agency), public space organization (i.e. Mercator, Copernicus) and private companies.
Among our projects (non-exhaustive list):
• the biggest Copernicus/Sentinel collaborative ground segment of Europe (www.collgs.lu), i.e. the data center of the Luxembourg Space Agency LSADC,
• the Data Archival, Management and Processing Services DAMPS (www.damps.info) for the ACRI-ST mother company on behalf of the European Space Agency ESA a service that covers together the 80 % of ESA EO data, the systematic production of Sentinel-3A data and the reprocessing of Sentinel 2 so far, the biggest reprocessing of the history for ACRI-ST then ESA, the reformatting of all ESA EO data in cloud-optimized format and their distribution on the Destinee digital platform @OVH, and the implementation of an AI-based EO application platform using resources of the Luxembourg HPC Meluxina.
The company owns a relevant infrastructure with reference disk storage capacity of 80PB, tape storage capacity of 200 PB, and a computing cluster with almost 1.2 Petaflops capacity. To meet the needs of our clients the infrastructure hosts multiple kinds of environment ranging from
dedicated HPC solutions to multi-hybrid cloud solutions.
The position to be filled
adwäisEO SA is looking for a talented AI Engineer to join its data team and support innovative Earth Observation data valorization. The AI Engineer role is centered around the survey, design, development and optimization of state-of-the-art machine learning and deep learning algorithms (i.e..GEO-FM/VLM/LLM,…) to enhance current workflow on EO imagery processing and environmental dataset and metadata generation. The candidate will work on the development of deep learning and AI processes to support the generation of innovative new data derived information. The activities will include the development of advanced models and pipelines such as foundation model for EO data, Vision transformers and attention-based architecture for multimodal dataset and scalable workflows leveraging High-Performance Computing (HPC).
She/he will be contributing to:
• Survey of and feedback on technological progress in the deep learning and machine learning technology evolution in the domain,
• Design and development of deep learning algorithms for EO imagery and related datasets
• Development of related documentation (Algorithm baseline, functional analysis)
• Definition of data requirement for processing chain.
• Writing engineering documentation and technical reports in English.
• Participation to the Bids and proposals.
Must Have Requirements
Profile
• 2-3 years of experience in deep learning and algorithm development (preferable for Remote Sensing or imagery/video data).
Technical Skills (Hard Skills)
• Experience with Deep Learning and/or Machine Learning techniques, attention-based architecture, foundation model, Vision and Large Language models in particular.
• Proficiency in python with solid object-oriented programming practices and experience building modular, scalable pipelines.
• Hands-on experience with popular deep learning frameworks (pytorch, tensorflow), specialized libraries (rasterio, xarray, geopandas, terratorch)
• Familiarity with Linux environments.
• Knowledge of Rest API for querying EO data repositories (e.g. STAC), with expertise in creating, validating, and maintaining robust training datasets.
Behavior skills (Soft Skills)
• Analytical, critical and proactive mind.
• Fluency in English (spoken and written) is essential.
• Very good organizational quality required.
• Very good communication skills.
• High degree of autonomy.
Being considered as a plus:
• Knowledge of other programming or coding languages such as IDL, C, C++.
• Experience with physical modelling (e.g. hydraulic, hydrology, crop, …)
• MLOps Skills (Docker, microservices)
• Experience with HPC, distributed training, or GPU-accelerated computation.
• Knowledge on Satellite data processing
• PostDoc in Remote Sensing or ML.
What we offer
• A professional, stimulating and human working environment in IT & Earth Observation Data
• sector based on proximity management,
• A real possibility of evolution depending on your involvement in your work,
• Lunch vouchers,
• Supplementary Health insurance,
• Bonuses,
• Canteen,
• Fitness room + shower,
• Pleasant premises in the heart of the Luxembourg countryside,
• Free car park
Why Join Us?
• Be part of innovative projects with strong impact in high-tech and strategic sectors.
• Work in an agile, ambitious environment at the heart of a fast-growing industry.
• Contribute to the development of cutting-edge solutions and help shape the future of our
• business.
• Join a dynamic and passionate team, committed to excellence and continuous improvement.
Other information
Starting date: as soon as possible
Workplace: Betzdorf (Luxembourg)
How to apply: Interested? sent CV, motivational letter to jobs@adwaiseo.eu
Job Types: Full-time, Permanent
Working from home: Remote working days are offered in line with current regulations (up to 34 days per year
Salary: depending on experience (The salary includes benefits, excluding exceptional bonuses).
Zaļenieku komerciālā un amatniecības vidusskola aicina darbā matemātikas skolotāju
Darba pienākumi
Veikt matemātikas skolotāja pienākumus pamatskolas un profesionālās izglītības programmās (vidusskolas posms).
Darba slodze
Pamatskolas posms – 0.9 slodze;
540 kontaktstundas mācību gadā.
Prasības kandidātiem
Izglītība atbilstoši MK noteikumiem Nr.569 "Noteikumi par pedagogiem nepieciešamo izglītību un profesionālo kvalifikāciju un pedagogu profesionālās kompetences pilnveides kārtību".
Piedāvājums
darba līgumu uz nenoteiktu laiku;
amatalgu 1410,00 Eur par slodzi pirms nodokļu nomaksas.
Piezīmes
CV un pieteikumu sūtīt uz zaleniekukav@jelgavasnovads.lv, tālrunis informācijai 28396446.
Ķeguma pamatskola aicina darbā vācu valodas skolotāju uz nenoteiktu laiku
Galvenie pienākumi:
• īstenot izglītības programmu, atbilstoši valsts izglītības standartam;
• plānot, organizēt un īstenot pedagoģisko darbu atbilstoši izglītības iestādē izvirzītajiem mērķiem;
• mācību stundas vadīt, izvēloties daudzveidīgas mācību metodes, atbilstoši konkrētajam vecuma posmam un mācību programmai;
• pielāgot mācību procesu skolēnu individuālajām vajadzībām un spējām, tai skaitā iekļaujošā izglītībā;
• sniegt skolēniem atgriezenisko saiti un vērtējumu par paveikto;
• ievērot izglītības iestādes noteikto darba kārtību un citus saistošos normatīvos aktus un ētikas normas.
Pieteikšanās kārtība:
Pieteikuma dokumentus – CV un pieteikuma vēstuli, lūdzam iesniegt līdz 2026.gada 31.augustam e-pasta adresē: skola@kegumaskola.lv, ilze.krastina@kegumaskola.lv Kontakttālrunis informācijai: 26414011.
Ķeguma pamatskola informē, ka pretendents iesūtot pieprasīto dokumentu kopumu, piekrīt personas datu apstrādei un pretendentu pieteikuma dokumentos norādītie personas dati tiks apstrādāti, lai nodrošinātu pretendentu izvērtēšanas procesa norisi.
